Comparative study of label and label-free techniques using shotgun proteomics for relative protein quantification

Advancing Nanomaterial Toxicology Screening Through Efficient and Cost-Effective Quantitative Proteomics

Proteomic investigations yield high-dimensional datasets, yet their application to large-scale toxicological assessments is hindered by reproducibility challenges due to fluctuating measurement conditions. To address these limitations, this study introduces an advanced tandem mass tag (TMT) labeling protocol. Although labeling approaches shorten data acquisition time by multiplexing samples compared to traditional label-free quantification (LFQ) methods in general, the associated costs may surge significantly with large sample sets, for example, in toxicological screenings. However, the introduced advanced protocol offers an efficient, cost-effective alternative, reducing TMT reagent usage (by a factor of ten) and requiring minimal biological material (1 µg), while demonstrating increased reproducibility compared to LFQ. To demonstrate its effectiveness, the advanced protocol is employed to assess the toxicity of nine benchmark nanomaterials (NMs) on A549 lung epithelial cells. While LFQ measurements identify 3300 proteins, they proved inadequate to reveal NM toxicity. Conversely, despite detecting 2600 proteins, the TMT protocol demonstrates superior sensitivity by uncovering alterations induced by NM treatment. In contrast to previous studies, the introduced advanced protocol allows simultaneous and straightforward assessment of multiple test substances, enabling prioritization, ranking, and grouping for hazard evaluation. Additionally, it fosters the development of New Approach Methodologies (NAMs), contributing to innovative methodologies in toxicological research.

A critical comparison of three MS-based approaches for quantitative proteomics analysis

MS-based proteomics is expanding its role as a routine tool for biological discovery. Nevertheless, the task of accurately and precisely quantifying thousands of analytes in a single experiment remains challenging. In this study, the diagnostic accuracy of three popular data-dependent methods for protein relative quantification (label-free [LF], dimethyl labelling [DML] and tandem mass tags [TMT]) has been assessed using a mixed species proteome (three species) and five experimental replicates per condition. Data were produced using a quadrupole-Orbitrap mass spectrometer and analysed using a single platform (the MaxQuant/Perseus software suite). The whole comparative analysis was repeated three times over a period of 6 months, in order to assess the consistency of the reported findings. As expected, label-based methods reproducibly provided a lower false positives rate, whereas TMT and LF performed similarly, and significantly better than DML, in terms of proteome coverage using the same instrument time. Although parameters like proteome coverage and precision were consistent in between replicates, other parameters like sensitivity, intended as the capacity of correctly classifying true positives (regulated proteins), were found to be less reproducible, especially at challenging fold-changes (1.5). Collectively, data suggest that an increased interest in data reproducibility would be desirable in the quantitative proteomics field.

A standard addition method to quantify histamine by reductive amination and hydrophilic interaction liquid chromatography coupled with tandem mass spectrometry

Histamine is an organic nitrogenous compound that acts as a neurotransmitter in the uterus, spinal cord, and brain and is involved in local immune responses. In this study, we developed a fast and simple derivatization method based on reductive amination that can be used to quantify histamine by hydrophilic interaction liquid chromatography coupled with tandem mass spectrometry. Histamine isotope analogs were synthesized via reductive amination. Histamine was modified with H₂-formaldehyde to form N-dimethylated histamine to act as a standard or with D₂-formaldehyde to form N-dimethylated histamine-d₄ to act as an internal standard. Using this method, we achieved a limit of detection of 3.6 ng/mL, a limit of quantification of 7.9 ng/mL, and a linear calibration curve with a coefficient of determination (R²) of 0.9987. Furthermore, the intra-day relative standard deviations ranged from 0.9% to 3.7% and the inter-day relative standard deviations ranged from 2.0% to 17.6%. After derivatization, N-dimethylated histamine showed 382.5% signal enhancement compared to unmodified histamine in mass spectrometry detection. To demonstrate the applicability of this method for biological samples, we utilized standard addition method to quantify histamine in fetal bovine serum and achieved a recovery of 86.7%.

Genome-wide proteomic profiling reveals the role of dominance protein expression in heterosis in immature maize ears

Heterosis refers to the phenomenon in which hybrid progeny show superior performance relative to their parents. Early maize ear development shows strong heterosis in ear architecture traits and greatly affects grain yield. To explore the underlying molecular mechanisms, genome-wide proteomics of immature ears of maize hybrid ZD909 and its parents were analyzed using tandem mass tag (TMT) technology. A total of 9,713 proteins were identified in all three genotypes. Among them, 3,752 (38.6%) proteins were differentially expressed between ZD909 and its parents. Multiple modes of protein action were discovered in the hybrid, while dominance expression patterns accounted for 63.6% of the total differentially expressed proteins (DEPs). Protein pathway enrichment analysis revealed that high parent dominance proteins mainly participated in carbon metabolism and nitrogen assimilation processes. Our results suggested that the dominant expression of favorable alleles related to C/N metabolism in the hybrid may be essential for ZD909 ear growth and heterosis formation. Integrated analysis of proteomic and quantitative trait locus (QTL) data further support our DEP identification and provide useful information for the discovery of genes associated with ear development. Our study provides comprehensive insight into the molecular mechanisms underlying heterosis in immature maize ears from a proteomic perspective.

LC-MS/MS quantification of sulfotransferases is better than conventional immunogenic methods in determining human liver SULT activities: implication in precision medicine

This study aims to determine whether enzyme activities are correlated with protein amounts and mRNA expression levels of five major human sulfotransferase (SULT) enzymes in 10 matched pericarcinomatous and hepatocellular carcinoma liver samples. The MRM UHPLC-MS/MS method, Western blot and RT-PCR were used along with SULT activity measurement using probe substrates. The LC-MS/MS method was specific for all five tested SULTs, whereas Western blot was specific for only two isoforms. The activities of SULT1A1, SULT1B1, SULT1E1 and SULT2A1 in 9 of 10 samples showed a significant decrease in tumor tissues relative to matched pericarcinomatous tissues, whereas the activities of SULT1A3 in 7 of 10 samples increased. The turnover numbers of SULTs did not change, except for SULT1A1. A generally high degree of correlations was observed between SULT activities and protein amounts (r² ≥ 0.59 except one), whereas a low degree of correlations was observed between SULT activities and mRNA expression levels (r² ≤ 0.48 except one). HCC reduced the SULT activities via impaired protein amounts. LC-MS/MS quantification of SULTs is highly reliable measurement of SULT activities, and may be adopted for implementing precision medicine with respect to drugs mainly metabolized by SULTs in healthy and HCC patients.

Assessment of Label-Free Quantification in Discovery Proteomics and Impact of Technological Factors and Natural Variability of Protein Abundance

We evaluated the state of label-free discovery proteomics focusing especially on technological contributions and contributions of naturally occurring differences in protein abundance to the intersample variability in protein abundance estimates in this highly peptide-centric technology. First, the performance of popular quantitative proteomics software, Proteome Discoverer, Scaffold, MaxQuant, and Progenesis QIP, was benchmarked using their default parameters and some modified settings. Beyond this, the intersample variability in protein abundance estimates was decomposed into variability introduced by the entire technology itself and variable protein amounts inherent to individual plants of the Arabidopsis thaliana Col-0 accession. The technical component was considerably higher than the biological intersample variability, suggesting an effect on the degree and validity of reported biological changes in protein abundance. Surprisingly, the biological variability, protein abundance estimates, and protein fold changes were recorded differently by the software used to quantify the proteins, warranting caution in the comparison of discovery proteomics results. As expected, ∼99% of the proteome was invariant in the isogenic plants in the absence of environmental factors; however, few proteins showed substantial quantitative variability. This naturally occurring variation between individual organisms can have an impact on the causality of reported protein fold changes.

Spinal Cord Stimulation Alters Protein Levels in the Cerebrospinal Fluid of Neuropathic Pain Patients: A Proteomic Mass Spectrometric Analysis

OBJECTIVES

Electrical neuromodulation by spinal cord stimulation (SCS) is a well-established method for treatment of neuropathic pain. However, the mechanism behind the pain relieving effect in patients remains largely unknown. In this study, we target the human cerebrospinal fluid (CSF) proteome, a little investigated aspect of SCS mechanism of action.

METHODS

Two different proteomic mass spectrometry protocols were used to analyze the CSF of 14 SCS responsive neuropathic pain patients. Each patient acted as his or her own control and protein content was compared when the stimulator was turned off for 48 hours, and after the stimulator had been used as normal for three weeks.

RESULTS

Eighty-six proteins were statistically significantly altered in the CSF of neuropathic pain patients using SCS, when comparing the stimulator off condition to the stimulator on condition. The top 12 of the altered proteins are involved in neuroprotection (clusterin, gelsolin, mimecan, angiotensinogen, secretogranin-1, amyloid beta A4 protein), synaptic plasticity/learning/memory (gelsolin, apolipoprotein C1, apolipoprotein E, contactin-1, neural cell adhesion molecule L1-like protein), nociceptive signaling (neurosecretory protein VGF), and immune regulation (dickkopf-related protein 3).

CONCLUSION

Previously unknown effects of SCS on levels of proteins involved in neuroprotection, nociceptive signaling, immune regulation, and synaptic plasticity are demonstrated. These findings, in the CSF of neuropathic pain patients, expand the picture of SCS effects on the neurochemical environment of the human spinal cord. An improved understanding of SCS mechanism may lead to new tracks of investigation and improved treatment strategies for neuropathic pain.

Comparing the Diagnostic Classification Accuracy of iTRAQ, Peak-Area, Spectral-Counting, and emPAI Methods for Relative Quantification in Expression Proteomics

Diagnostic classification accuracy is critical in expression proteomics to ensure that as many true differences as possible are identified with acceptable false-positive rates. We present a comparison of the diagnostic accuracy of iTRAQ with three label-free methods, peak area, spectral counting, and emPAI, for relative quantification using a spiked proteome standard. We provide the first validation of emPAI for intersample relative quantification and find clear differences among the four quantification approaches that could be considered when designing an experiment. Spectral counting was observed to perform surprisingly well in all regards. Peak area performed best for smaller fold differences and was shown to be capable of discerning a 1.1-fold difference with acceptable specificity and sensitivity. The performance of iTRAQ was dramatically worse than the label-free methods with low abundance proteins. Using the iTRAQ data set for validation, we also demonstrate a novel iTRAQ analysis regime that avoids the use of ratios in significance testing and outperforms a common commercial alternative.

A novel reductive amination method with isotopic formaldehydes for the preparation of internal standard and standards for determining organosulfur compounds in garlic

Garlic (Allium sativum) is a long-cultivated plant that is widely utilized in cooking and has been employed as a medicine for over 4000 years. In this study, we fabricated standards and internal standards (ISs) for absolute quantification via reductive amination with isotopic formaldehydes. Garlic has four abundant organosulfur compounds (OSCs): S-allylcysteine, S-allylcysteinine sulfoxide, S-methylcysteine, and S-ethylcysteine are abundant in garlic. OSCs with primary amine groups were reacted with isotopic formaldehydes to synthesize ISs and standards. Cooked and uncooked garlic samples were compared, and we utilized tandem mass spectrometry equipped with a selective reaction monitoring technique to absolutely quantify the four organosulfur compounds.

Comparative Analysis of Label-Free and 8-Plex iTRAQ Approach for Quantitative Tissue Proteomic Analysis

High resolution proteomics approaches have been successfully utilized for the comprehensive characterization of the cell proteome. However, in the case of quantitative proteomics an open question still remains, which quantification strategy is best suited for identification of biologically relevant changes, especially in clinical specimens. In this study, a thorough comparison of a label-free approach (intensity-based) and 8-plex iTRAQ was conducted as applied to the analysis of tumor tissue samples from non-muscle invasive and muscle-invasive bladder cancer. For the latter, two acquisition strategies were tested including analysis of unfractionated and fractioned iTRAQ-labeled peptides. To reduce variability, aliquots of the same protein extract were used as starting material, whereas to obtain representative results per method further sample processing and MS analysis were conducted according to routinely applied protocols. Considering only multiple-peptide identifications, LC-MS/MS analysis resulted in the identification of 910, 1092 and 332 proteins by label-free, fractionated and unfractionated iTRAQ, respectively. The label-free strategy provided higher protein sequence coverage compared to both iTRAQ experiments. Even though pre-fraction of the iTRAQ labeled peptides allowed for a higher number of identifications, this was not accompanied by a respective increase in the number of differentially expressed changes detected. Validity of the proteomics output related to protein identification and differential expression was determined by comparison to existing data in the field (Protein Atlas and published data on the disease). All methods predicted changes which to a large extent agreed with published data, with label-free providing a higher number of significant changes than iTRAQ. Conclusively, both label-free and iTRAQ (when combined to peptide fractionation) provide high proteome coverage and apparently valid predictions in terms of differential expression, nevertheless label-free provides higher sequence coverage and ultimately detects a higher number of differentially expressed proteins. The risk for receiving false associations still exists, particularly when analyzing highly heterogeneous biological samples, raising the need for the analysis of higher sample numbers and/or application of adjustment for multiple testing.

Micellar extraction possesses a new advantage for the analysis of Alzheimer's disease brain proteome

Integral membrane proteins (MPs), such as transporters, receptors, and ion channels, are of great interest because of their participation in various vital cellular functions including cell-cell interactions, ion transport, and signal transduction. However, studies of MPs are complicated because of their hydrophobic nature, heterogeneity, and low abundance. Cloud-point extraction (CPE) with the non-ionic surfactant Triton X-114 was performed to simultaneously extract and phase separate hydrophobic and hydrophilic proteins from Alzheimer's disease (AD) and unaffected control brain tissue. Quantitative proteomics analysis of temporal neocortex samples of AD patients and controls was performed using a shotgun approach based on stable isotope dimethyl labeling (DML) quantification technique followed by nanoLC-MS/MS analysis. A total of 1096 unique proteins were identified and quantified, with 40.3 % (211/524) predicted as integral MPs with at least one transmembrane domain (TMD) found in the detergent phase, and 10 % (80/798) in the detergent-depleted phase. Among these, 62 proteins were shown to be significantly altered (p-value <0.05), in AD versus control samples. In the detergent fraction, we found 10 hydrophobic transmembrane proteins containing up to 14 putative TMDs that were significantly up- or down-regulated in AD compared with control brains. Changes in four of these proteins, alpha-enolase (ENOA), lysosome-associated membrane glycoprotein 1 (LAMP1), 14-3-3 protein gamma (1433G), and sarcoplasmic/endoplasmic reticulum calcium ATPase2 (AT2A2) were validated by immunoblotting. Our results emphasize that separating hydrophobic MPs in CPE contributes to an increased understanding of the underlying molecular mechanisms in AD. Such knowledge can become useful for the development of novel disease biomarkers.

A proteomic approach to monitor the dynamic response of the female oviductal epithelial cell surface to male gametes

Sophisticated strategies to analyze cell surface proteins are indispensable to study fundamental biological processes, such as the response of cells to environmental changes or cell-cell communication. Herein, we describe a refined mass spectrometry-based approach for the specific characterization and quantitation of cell surface proteins expressed in the female reproductive tract. The strategy is based on in situ biotinylation of rabbit oviducts, affinity enrichment of surface exposed biotin tagged proteins and dimethyl labeling of the obtained tryptic peptides followed by LC-MS/MS analysis. This approach proved to be sensitive enough to analyze small sample amounts (<1μg) and allowed further to trace the dynamic composition of the surface proteome of the oviductal epithelium in response to male gametes. The relative protein expression ratios of 175 proteins were quantified. Thirty-one of them were found to be altered over time, namely immediately, 1h and 2h after insemination compared to the time-matched control groups. Functional analysis demonstrated that structural reorganization of the oviductal epithelial cell surface was involved in the early response of the female organ to semen. In summary, this study outlines a workflow that is capable to monitor alterations in the female oviduct that are related to key reproductive processes in vivo.

BIOLOGICAL SIGNIFICANCE

The proper interaction between the female reproductive tract, in particular, the oviduct and the male gametes, is fundamental to fertilization and embryonic development under physiological conditions. Thereby the oviductal epithelial cell surface proteins play an important role. Besides their direct interaction with male gametes, these molecules participate in signal transduction and, thus, are involved in the mandatory cellular response of the oviductal epithelium. In this study we present a refined LC-MS/MS based workflow that is capable to quantitatively analyze the expression of oviductal epithelial cell surface proteins in response to insemination in vivo. A special focus was on the very early interaction between the female organ and the male gametes. At first, this study clearly revealed an immediate response of the surface proteome to semen, which was modulated over time. The described methodology can be applied for studies of further distinct biological events in the oviduct and therefore contribute to a deeper insight into the formation of new life.

Accessing microenvironment compartments in formalin-fixed paraffin-embedded tissues by protein expression analysis

BACKGROUND

Formalin-fixed paraffin-embedded (FFPE) samples are an outstanding source of new information regarding disease evolvements. Current research on new biomarkers and diseases features has recently invested resources in FFPE-related projects.

RESULTS

In order to initiate clinical protein-expression studies using minute amount of biological material, a workflow based on the combination of filter-assisted sample preparation with MS analysis and label-free quantification was developed. Xenograft lung tumor tissue was investigated as a model system. The workflow was optimized and characterized in terms of its reproducibility from a quantitative and qualitative point of view. We proposed a modification of the original filter-assisted sample preparation protocol to improve reproducibility and highlight its potential for the investigation of hydrophobic proteins.

CONCLUSIONS

Altogether the presented workflow allows analysis of FFPE samples with improvements in the analytical time and performance, and we show its application for lung cancer xenograft tissue samples.

Exploiting the proteomics revolution in biotechnology: from disease and antibody targets to optimizing bioprocess development

Recent advancements in proteomics have enabled the generation of high-quality data sets useful for applications ranging from target and monoclonal antibody (mAB) discovery to bioprocess optimization. Comparative proteomics approaches have recently been used to identify novel disease targets in oncology and other disease conditions. Proteomics has also been applied as a new avenue for mAb discovery. Finally, CHO and Escherichia coli cells represent the dominant production hosts for biopharmaceutical development, yet the physiology of these cells types has yet to be fully established. Proteomics approaches can provide new insights into these cell types, aiding in recombinant protein production, cell growth regulation, and medium formulation. Optimization of sample preparations and protein database developments are enhancing the quantity and accuracy of proteomic results. In these ways, innovations in proteomics are enriching biotechnology and bioprocessing research across a wide spectrum of applications.

Quantification of the brain proteome in Alzheimer's disease using multiplexed mass spectrometry

We have compared the brain proteome in the temporal neocortex between Alzheimer's disease (AD) patients and non-AD individuals by using shotgun mass spectrometry based on a stable isotope dimethyl labeling. A total of 827 unique proteins were identified and quantitated. Of these, 227 proteins were found in at least 9 out of 10 AD/control pairs and were further subjected to statistical analysis. A total of 69 proteins showed different levels (p-value < 0.05) in AD versus control brain samples. Of these proteins, 37 were increased and 32 were decreased as compared to the non-AD subjects. Twenty-three proteins comprise novel proteins that have not previously been reported as related to AD, e.g., neuronal-specific septin-3, septin-2, septin-5, dihydropteridine reductase, and clathrin heavy chain 1. The proteins with altered levels in the AD brain represent a wide variety of pathways suggested to be involved in the disease pathogenesis, including energy metabolism, glycolysis, oxidative stress, apoptosis, signal transduction, and synaptic functioning. Apart from leading to new insights into the molecular mechanisms in AD, the findings provide us with possible novel candidates for future diagnostic and prognostic disease markers.

Recent advances in molecular imaging of premalignant gastrointestinal lesions and future application for early detection of barrett esophagus

Recent advances in optical molecular imaging allow identification of morphologic and biochemical changes in tissues associated with gastrointestinal (GI) premalignant lesions earlier and in real-time. This focused review series introduces high-resolution imaging modalities that are being evaluated preclinically and clinically for the detection of early GI cancers, especially Barrett esophagus and esophageal adenocarcinoma. Although narrow band imaging, autofluorescence imaging, and chromoendoscopy are currently applied for this purpose in the clinic, further adoptions of probe-based confocal laser endomicroscopy, high-resolution microendoscopy, optical coherence tomography, and metabolomic imaging, as well as imaging mass spectrometry, will lead to detection at the earliest and will guide predictions of the clinical course in the near future in a manner that is beyond current advancements in optical imaging. In this review article, the readers will be introduced to sufficient information regarding this matter with which to enjoy this new era of high technology and to confront science in the field of molecular medical imaging.